{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ef1ab3ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "#设置中文编码和负号的正常显示\n",
    "plt.rcParams['font.family']='Microsoft YaHei'\n",
    "plt.rcParams['axes.unicode_minus'] = False\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "61bfb866",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取数据\n",
    "file_path='D:\\大二上\\\\EducationData.xlsx'\n",
    "lr_data=pd.read_excel(file_path,'Literacy rate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "79b4e5ea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                          Female         Male\n",
      "Development Regions                          \n",
      "Least Developed      2523.132982  2882.878162\n",
      "Less Developed       8496.374615  8691.346779\n",
      "More Developed       2374.845985  2378.052559\n",
      "Not Classified          0.000000     0.000000\n"
     ]
    }
   ],
   "source": [
    "df = pd.DataFrame(lr_data)\n",
    "# 创建数据透视表，以国家发展程度为索引，计算男女识字率\n",
    "pivot = df.pivot_table(index='Development Regions', values=['Male','Female'], aggfunc='sum') \n",
    "# 输出结果\n",
    "print(pivot)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e58bdedd",
   "metadata": {},
   "source": [
    "### 1.3.1绘制不同国家发展程度中男女识字率的柱状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "824b42cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/v5/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"80fbd65b47c544ab99e63fa90bb07c34\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_80fbd65b47c544ab99e63fa90bb07c34 = echarts.init(\n",
       "                    document.getElementById('80fbd65b47c544ab99e63fa90bb07c34'), 'white', {renderer: 'canvas'});\n",
       "                var option_80fbd65b47c544ab99e63fa90bb07c34 = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"aria\": {\n",
       "        \"enabled\": false\n",
       "    },\n",
       "    \"color\": [\n",
       "        \"#5470c6\",\n",
       "        \"#91cc75\",\n",
       "        \"#fac858\",\n",
       "        \"#ee6666\",\n",
       "        \"#73c0de\",\n",
       "        \"#3ba272\",\n",
       "        \"#fc8452\",\n",
       "        \"#9a60b4\",\n",
       "        \"#ea7ccc\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u7537\\u6027\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                2882.878162,\n",
       "                8691.346779,\n",
       "                2378.052559\n",
       "            ],\n",
       "            \"realtimeSort\": false,\n",
       "            \"showBackground\": false,\n",
       "            \"stackStrategy\": \"samesign\",\n",
       "            \"cursor\": \"pointer\",\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": false,\n",
       "                \"margin\": 8\n",
       "            },\n",
       "            \"markPoint\": {\n",
       "                \"label\": {\n",
       "                    \"show\": true,\n",
       "                    \"position\": \"inside\",\n",
       "                    \"color\": \"#fff\",\n",
       "                    \"margin\": 8\n",
       "                },\n",
       "                \"data\": [\n",
       "                    {\n",
       "                        \"name\": \"\\u6700\\u5c0f\\u503c\",\n",
       "                        \"type\": \"min\"\n",
       "                    },\n",
       "                    {\n",
       "                        \"name\": \"\\u6700\\u5927\\u503c\",\n",
       "                        \"type\": \"max\"\n",
       "                    },\n",
       "                    {\n",
       "                        \"name\": \"\\u5e73\\u5747\\u503c\",\n",
       "                        \"type\": \"average\"\n",
       "                    }\n",
       "                ]\n",
       "            },\n",
       "            \"rippleEffect\": {\n",
       "                \"show\": true,\n",
       "                \"brushType\": \"stroke\",\n",
       "                \"scale\": 2.5,\n",
       "                \"period\": 4\n",
       "            }\n",
       "        },\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u5973\\u6027\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                2378.052559,\n",
       "                8496.374615,\n",
       "                2374.845985\n",
       "            ],\n",
       "            \"realtimeSort\": false,\n",
       "            \"showBackground\": false,\n",
       "            \"stackStrategy\": \"samesign\",\n",
       "            \"cursor\": \"pointer\",\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": false,\n",
       "                \"margin\": 8\n",
       "            },\n",
       "            \"markPoint\": {\n",
       "                \"label\": {\n",
       "                    \"show\": true,\n",
       "                    \"position\": \"inside\",\n",
       "                    \"color\": \"#fff\",\n",
       "                    \"margin\": 8\n",
       "                },\n",
       "                \"data\": [\n",
       "                    {\n",
       "                        \"name\": \"\\u6700\\u5c0f\\u503c\",\n",
       "                        \"type\": \"min\"\n",
       "                    },\n",
       "                    {\n",
       "                        \"name\": \"\\u6700\\u5927\\u503c\",\n",
       "                        \"type\": \"max\"\n",
       "                    },\n",
       "                    {\n",
       "                        \"name\": \"\\u5e73\\u5747\\u503c\",\n",
       "                        \"type\": \"average\"\n",
       "                    }\n",
       "                ]\n",
       "            },\n",
       "            \"rippleEffect\": {\n",
       "                \"show\": true,\n",
       "                \"brushType\": \"stroke\",\n",
       "                \"scale\": 2.5,\n",
       "                \"period\": 4\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u7537\\u6027\",\n",
       "                \"\\u5973\\u6027\"\n",
       "            ],\n",
       "            \"selected\": {},\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14,\n",
       "            \"backgroundColor\": \"transparent\",\n",
       "            \"borderColor\": \"#ccc\",\n",
       "            \"borderWidth\": 1,\n",
       "            \"borderRadius\": 0,\n",
       "            \"pageButtonItemGap\": 5,\n",
       "            \"pageButtonPosition\": \"end\",\n",
       "            \"pageFormatter\": \"{current}/{total}\",\n",
       "            \"pageIconColor\": \"#2f4554\",\n",
       "            \"pageIconInactiveColor\": \"#aaa\",\n",
       "            \"pageIconSize\": 15,\n",
       "            \"animationDurationUpdate\": 800,\n",
       "            \"selector\": false,\n",
       "            \"selectorPosition\": \"auto\",\n",
       "            \"selectorItemGap\": 7,\n",
       "            \"selectorButtonGap\": 10\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"enterable\": false,\n",
       "        \"confine\": false,\n",
       "        \"appendToBody\": false,\n",
       "        \"transitionDuration\": 0.4,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5,\n",
       "        \"order\": \"seriesAsc\"\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": true,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"Least Developed\",\n",
       "                \"Less Developed\",\n",
       "                \"More Developed\",\n",
       "                \"Not Classified\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": true,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"text\": \"\\u4e0d\\u540c\\u56fd\\u5bb6\\u53d1\\u5c55\\u7a0b\\u5ea6\\u4e2d\\u7537\\u5973\\u8bc6\\u5b57\\u7387\\u5bf9\\u6bd4\\u60c5\\u51b5\",\n",
       "            \"target\": \"blank\",\n",
       "            \"subtext\": \"\\u67f1\\u72b6\\u56fe\",\n",
       "            \"subtarget\": \"blank\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"textAlign\": \"auto\",\n",
       "            \"textVerticalAlign\": \"auto\",\n",
       "            \"triggerEvent\": false\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_80fbd65b47c544ab99e63fa90bb07c34.setOption(option_80fbd65b47c544ab99e63fa90bb07c34);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x24be1477880>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyecharts import options as opts\n",
    "from pyecharts.charts import *\n",
    "\n",
    "x_index = [\"Least Developed\",\"Less Developed\",\"More Developed\",\"Not Classified\"]\n",
    "man = [2882.878162, 8691.346779,2378.052559]\n",
    "woman= [2378.052559,8496.374615,2374.845985]\n",
    "\n",
    "\n",
    "bar = (\n",
    "    Bar()\n",
    "    .add_xaxis(x_index)\n",
    "    .add_yaxis(\"男性\",man) # y轴设置\n",
    "    .add_yaxis(\"女性\",woman) # y轴设置\n",
    "    .set_global_opts(title_opts=opts.TitleOpts(title=\"不同国家发展程度中男女识字率对比情况\", subtitle=\"柱状图\"))\n",
    "    .set_series_opts(label_opts=opts.LabelOpts(is_show=False),\n",
    "                    markpoint_opts=opts.MarkPointOpts(\n",
    "                        data=[\n",
    "                opts.MarkPointItem(type_=\"min\", name=\"最小值\"),\n",
    "                opts.MarkPointItem(type_=\"max\", name=\"最大值\"),\n",
    "                opts.MarkPointItem(type_=\"average\", name=\"平均值\")])\n",
    "                    )\n",
    "    )\n",
    "\n",
    "bar.render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "145a235d",
   "metadata": {},
   "source": [
    "### 1.3.2绘制识字能力占比直方图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "6ba03a7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '分布直方图')"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(lr_data['Total'],bins=10,edgecolor=\"c\",histtype=\"bar\",alpha=0.5)\n",
    "plt.xlabel(\"识字能力总百分比区间\")\n",
    "plt.title('分布直方图')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a8f44ee",
   "metadata": {},
   "source": [
    "### 1.3.3绘制热力图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "8b654f41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 计算相关性\n",
    "a = lr_data.corr()\n",
    "# 绘制相关性热力图\n",
    "plt.figure(figsize=(8, 5))\n",
    "\n",
    "sns.heatmap(a, annot=True, cmap=\"BuGn\", linewidths=0.2, fmt='.2f')\n",
    "plt.title('相关性热力图')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5670d68f",
   "metadata": {},
   "source": [
    "### 1.3.4 绘制不同年龄的男性箱线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "019aa9d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Age Range', ylabel='Male'>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxenplot(x=\"Age Range\", y=\"Male\", data=lr_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d99599c9",
   "metadata": {},
   "source": [
    "###  1.3.5 绘制不同年龄的女性箱线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "5747c4bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Age Range', ylabel='Female'>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxenplot(x=\"Age Range\", y=\"Female\", data=lr_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1c0fa15",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
